Comparison
local-deep-research vs ollama
Verdict
Pick local-deep-research when local-deep-research is primarily Python; ollama is Go; pick ollama when ollama is primarily Go; local-deep-research is Python.
Markdown twin · local-deep-research alternatives · ollama alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | local-deep-research | ollama |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Very active (1d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of 3d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of today · osv@v1 | Published findings As of 3d · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- local-deep-research
- ~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encryp
- ollama
- Get up and running with various large language models using Ollama.
Stars
- local-deep-research
- 8.7k
- ollama
- 176k
Forks
- local-deep-research
- 767
- ollama
- 17k
Open issues
- local-deep-research
- 281
- ollama
- 3.4k
Language
- local-deep-research
- Python
- ollama
- Go
Adopt for
- local-deep-research
- -
- ollama
- Ollama is a Go-based platform that provides tools for deploying and managing large language models (LLMs) like Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma using docker images, package managers, cloud and
Persona
- local-deep-research
- -
- ollama
- -
Runtime
- local-deep-research
- -
- ollama
- -
License
- local-deep-research
- MIT
- ollama
- MIT license - permissive open-source licensing that allows for broad use of the tool.
Last pushed
- local-deep-research
- Jul 15, 2026
- ollama
- Jul 10, 2026
Categories
- local-deep-research
- Data & Retrieval, Inference & Serving, LLM Frameworks
- ollama
- Inference & Serving, LLM Frameworks
Trust and health
Days since push
- local-deep-research
- 0d
- ollama
- 1d
Open issues (now)
- local-deep-research
- 281
- ollama
- 3.4k
Owner type
- local-deep-research
- User
- ollama
- Organization
OSV dependency advisories
- local-deep-research
- No lockfile (source not queried)
- ollama
- Published findings
Full report
- local-deep-research
- Trust report
- ollama
- Trust report
Choose local-deep-research if…
- local-deep-research is primarily Python; ollama is Go.
- Tags unique to local-deep-research: academia, anthropic, arxiv, brave.
- Also covers Data & Retrieval.
When NOT to use local-deep-research
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Choose ollama if…
- ollama is primarily Go; local-deep-research is Python.
- Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers.
- Tags unique to ollama: deepseek, gemma, glm, go.
- ollama ships Docker support for self-hosted deployment.
- Use Ollama when you require a multi-model platform supporting several large language models such as Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and intend to deploy in various cloud or
When NOT to use ollama
- Avoid using Ollama if you are only interested in a single LLM deployment and seek simplified, model-specific solutions with tailored support rather than a comprehensive multi-model platform.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (LearningCircuit/local-deep-research) · observed Jul 15, 2026
- GitHub forks (LearningCircuit/local-deep-research) · observed Jul 15, 2026
- Last push (LearningCircuit/local-deep-research) · observed Jul 15, 2026
- License file (MIT) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (ollama/ollama) · observed Jul 11, 2026
- GitHub forks (ollama/ollama) · observed Jul 11, 2026
- Last push (ollama/ollama) · observed Jul 10, 2026
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: local-deep-research 8.7k · ollama 176k (synced Jul 15, 2026).
Common questions
- What is the difference between local-deep-research and ollama?
- local-deep-research: ~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encryp. ollama: Get up and running with various large language models using Ollama.. See the comparison table for live GitHub stats and shared categories.
- When should I choose local-deep-research over ollama?
- Choose local-deep-research over ollama when local-deep-research is primarily Python; ollama is Go; Tags unique to local-deep-research: academia, anthropic, arxiv, brave; Also covers Data & Retrieval.
- When should I choose ollama over local-deep-research?
- Choose ollama over local-deep-research when ollama is primarily Go; local-deep-research is Python; Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers; Tags unique to ollama: deepseek, gemma, glm, go; ollama ships Docker support for self-hosted deployment; Use Ollama when you require a multi-model platform supporting several large language models such as Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and intend to deploy in various cloud or.
- When should I avoid local-deep-research?
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- When should I avoid ollama?
- Avoid using Ollama if you are only interested in a single LLM deployment and seek simplified, model-specific solutions with tailored support rather than a comprehensive multi-model platform.
- Is local-deep-research or ollama more popular on GitHub?
- ollama has more GitHub stars (175,936 vs 8,719). Stars measure visibility, not whether either tool fits your constraints.
- Are local-deep-research and ollama open source?
- Yes - both are open-source projects on GitHub (local-deep-research: MIT, ollama: MIT).
- Where can I find alternatives to local-deep-research or ollama?
- GraphCanon lists graph-backed alternatives at local-deep-research alternatives and ollama alternatives (local-deep-research markdown twin, ollama markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, local-deep-research or ollama?
- local-deep-research: Very active. ollama: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for local-deep-research and ollama?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: local-deep-research trust report; ollama trust report.